I am delighted that Montclair State University (MSU) has won its bid to take over New Jersey public television, for in this moment I see an opening to reimagine and reinvent public media in a new image — as the public’s media.
And nowhere better for that to happen than in New Jersey, where threads have been coming together over years — most running through MSU — to support and grow the broader news ecosystem in the state. This support has come from private-public partnerships working with the university in what we have come to call the New Jersey Model.
Adding public television adds one more piece. Montclair State has first-rate television facilities and the chance to involve students and faculty in producing content for the channels. But to me, television is the least of it.
What really excites me is that Montclair has the opportunity to build on the strong foundation of its NJ News Commons and Center for Cooperative Media, which now serve more than 300 independent, community-based news providers, new and old, small and large.
Here I want to tell you the story of how this has evolved from what I have seen. I don’t mean to paint myself as a Zelig of the tale, as most often, I merely witnessed and cheered what has been happening. But I have been proud to have had the opportunity to watch as a new vision for local news, media, and community has been built here — a vision I’ve long believed in. I am also proud to say that I am a fellow at MSU’s Center for Cooperative Media, where I hope to help work toward that vision.
For me, this saga goes back three decades, when I began beating the drum for thinking of news through the lenses of ecosystems and communities over newsrooms and corporations. I was doing that while working as president and creative director of Advance.net, where we started NJ.com while developing hyperlocal news, and then in my research on news ecosystems and innovation at CUNY.
In New Jersey, this history stretches back at least as far a 2011, when then-Governor Christie sold off the state’s public media — and bandwidth in an FCC spectrum auction — to plug a budget hole. It was a short-sighted decision that robbed the state of its only broadcast outlets. The president of Montclair State at the time, Susan Cole, very much wanted to take over NJ’s public media. The state instead gave the TV and radio stations to WNET and WNYC in New York and WHYY in Philadelphia.
When that happened, an emergency meeting was convened in Newark with journalists and political leaders brought together to consider what to do about our state and news. Some wanted to start a newsroom. I instead beat my ecosystem drum, arguing that we had the chance to support the growth of news outlets in communities across the state, now made possible by the internet.
Soon, the Dodge Foundation — where I was an advisor and would serve for a time on the board — convinced Montclair State that it had the chance to support and grow the state’s independent and open news ecosystem with the creation of the NJ News Commons, headed at first by hyperlocal blogger Debbie Galant. At Advance, I had tried to persuade Debbie to start a Montclair blog on our site. “Good idea, Jeff,” she said. “But why the hell would I do that for you?” She was right. Instead, she founded Baristanet, a pioneering, independent hyperlocal blog that lives on in a merger that is now Montclair Local.
Debbie had the trust of the ragtag bunch of very independent local bloggers who were trying to make a go of it covering their towns online — and who frankly did not trust big, old news media. The Commons’ mission was to support those local news outlets with training, mentorship, and collaboration — not to compete with them by making a newsroom and content with it.
The Commons led, in turn to the founding of the Center for Cooperative Media, which under the leadership and vision of Stefanie Murray has been doing pathbreaking work. The Center has just launched a news-sharing network across the state’s ecosystem, funded by the Google News Initiative. It conducts research on communities’ information needs. It helps local news sites with their business and technology and it brings them together for collaborative projects. This is the foundation on which the real public media of New Jersey — the public’s media — is already being built.
After Christie denuded New Jersey’s media, the legislature was lobbied (read: guilted) to fund support for New Jersey news with the creation of the NJ Civic Information Consortium, which gives grants to applicants from across the state that meet its criteria for supporting the information needs of under-served communities and developing new models for sustainable news.
Together Montclair State’s Center and the Consortium — working with the hundreds of outlets in the state — have demonstrated what could be done when private and public, journalistic and academic entities work together for the good of communities. Back then, Tom Glaisyer of the Democracy Fund, dubbed what was happening here the New Jersey Model, and he vowed to spread it to other states in the nation.
I’ve testified about the New Jersey Model before legislators in California, Oregon, and Illinois as I’ve tried to dissuade them from passing legislation written by lobbyists for the old, hedge-fund-controlled newspaper industry as it seeks handouts via protectionist, retributive taxes aimed at tech companies. Instead, I say, look at what Jersey has done to build something bigger and better, more open, inclusive, and innovative, by offering support to folks who want to cover and serve their communities.
To be clear, I am not suggesting that old media should be left out of this future. I just joined the board of the not-for-profit that acquired NJ Hills Media, a chain of local weekly papers and sites. Through the Montclair State connection, NJ Hills is reaping benefits from the connection.
Enter MSU’s Professor Carrie Brown. We worked together at CUNY to build a new program in engagement journalism that she directed, centering communities and their priorities in students’ work. Both of us left CUNY and came to Montclair, where Carrie is bringing the values of the movement she has pioneered to classes and to the ecosystem.
In the latest term, Carrie had her engagement students go to listen to residents of Parsippany, where NJ Hills just started a new, online-only and free news site. A few weeks ago, the students presented the reporter covering the town, Nicole Flanagan, and her boss, NJ Hills CEO and publisher Joe Territo, with their findings and recommendations for coverage. Halfway through the presentations, Joe turned to me, saying he wanted help like that in every one of the towns the company covers.
Meanwhile, at Montclair, we are looking at other new programs, including potentially working with libraries in towns across the state as information hubs for their communities. That, too, is part of New Jersey’s news ecosystem.
This is the environment into which the new New Jersey public media fits. Stefanie Murray, alongside Keith Strudler, dean of MSU’s College of Communication and Media, and the university’s president, Jonathan Koppell, created the winning bid to convince the state to bring our stations back to our air after WNET decided to drop its franchise. I had no role in the process, other than getting to read and comment on the proposal in progress. I am confident that MSU’s team will use this opportunity to bring imagination, innovation, and inclusion to the task.
Here is Strudler illustrating how this all comes together around MSU’s vision of the public’s media:
We’ll have staff reporters — North, Central and South Jersey coverage to start, with a full-time Trenton reporter as an aspiration. But the bigger story is what’s already out there. There are hundreds of content creators across New Jersey — people doing serious storytelling on YouTube, TikTok, Instagram, local news sites — who already have audiences and are already doing good work. Our goal, working with the Center for Cooperative Media, is to figure out how we partner with those people. How we give them a bigger platform. How we extend our reach without pretending we can do everything ourselves….
The Center for Cooperative Media has been better than almost anyone in the country at building networks of storytellers across platforms. That’s going to be a real asset. And the best approach is to go to those communities and ask what they need — not come in from the top down and say we know what New Jersey wants.
Amen.
This is also a chance to rethink television. In the long-ago, I was TV critic for People and TV Guide, and so I have opinions. That is why, in the mid-1990s, my frequent boss and mentor Jim Willse — former editor and publisher of the NY Daily News, later to be the editor of Advance’s Star-Ledger — brought me in to consult on a project to launch a 24-hour news channel in NJ. I devised an eccentric content plan that proposed building the studio in New Jersey’s real main street — a mall. And so we could hear the voice of the people, I borrowed an idea from Canadian TV pioneer Moses Znaimer, whose CityTV built a “speakers’ corner” on a Toronto street, so anyone could record a message that might be included in a TV show. What became News12 New Jersey did build a kiosk to capture vox pop and parked it in a mall, for a little while, until Advance left the project.
Of course, today, we have the ultimate speakers’ corner in the internet, where even with its problems, communities can come together to share knowledge and need. Journalism should begin by listening to them. This is where and this is when the public’s media can be built, here in my home state, Jersey.
Artificial Intelligence, though more than a half-century old as a technology, has occupied front-of-mind cultural consciousness for only a few years, since ChatGPT. Yet AI is already profoundly disliked and distrusted in both media meme and apparently in public opinion.
The techlash against the internet and then social media took at least two decades to ferment, while the AI backlash feels more like an instant reflex. Fifty-seven percent of Americans say AI’s risks outweigh its benefits, making it less popular even than ICE! Half fret about its ill effects on creativity, meaningful relationships, news, and elections. In rare consensus, Republicans and Democrats alike are NIMBYing data centersacross the nation. A German digital conference offers a workshop in poisoning AI data. The FT declares “a new Luddite movement.” And commencement speakers daring to utter the letters A and I are sure to be booed.
It is, however, difficult to discern true public opinion from performative public opinion polls, as polls reflect media’s self-fulfilled prophesies. In reality, even as views of AI sour, the public’s use of the tools soars: more than half now employ it to, for example, research topics of interest, a thirty-eight percent increase in a year.
Who or what is to blame for AI’s bad rep? In The Web We Weave, I assert that the problem is less the AI than certain AI boys who make up the newest oligopoly. Look no farther than the now-finished OpenAI trial: technology’s Godzilla v. Mothra, unlikeable Musk v. unreliable Altman. Now add the creepy dramatis potens of West Coast billionaires (before they all dodge taxes and move to Miami) — Thiel, Andreessen, Karp, Zuck, Ellison, Bezos — plus the moral entrepreneurs trying to pump and exploit technofear (Tristan Harris, Eliezer Yudkowsky, Nick Bostrom, William MacAskill, Dustin Moskovitz) — and it’s no wonder people profess dislike for their algorithmic progeny. And it doesn’t help relations when they dismiss us humans as “meat computers.”
Yet AI is amazing, constantly wowing even the skeptical with its feats and tricks. Every week on the two (yes, two) AI podcasts I co-host — AI Inside and Intelligent Machines — I both both marvel at and fault the capabilities and implications of this new and powerful technology. Because I am also editing a new Bloomsbury book series about AI and humanity, I am constantly trying to get my head around how AI works, what it can and cannot do, what its benefits and perils might be, and what its creation, use, and product says about us as humans.
To learn more about AI, I do not turn to the boys above. I turn to critics, yes; there are many. But to understand AI’s innards I find it best to look to a few of the field’s master communicators and teachers, notably Jensen Huang, founder and CEO of Nvidia, and Yann LeCun, NYU professor and founder of the new AMI Labs. Unlike AI’s blind proselytizers, they do not market superheated claims of superintelligence a day away, nor in the doomsters’ dire warnings of AI-combusted human extinction.
Below are videos of each; dip in and you will learn more about AI.
Each man has clear economic interest in the success of AI; Huang leads the world’s largest corporation by market valuation and LeCun has raised $1 billion to envision a next generation of AI, past LLMs. Each tries to present realistic and credible perspectives on the present and near-future state of the art and technic of AI. Each calls bullshit on others when warranted. The most important reason I watch these two is because in their public appearances, each educates, addressing multilayered constituencies: customers, partners, investors, employees, policymakers, journalists, students, and the public.
I am fascinated by their presentation skills because, as a journalist, we’re supposed to be communicators. They also interest me because I am a visiting professor at Stony Brook University, where I work with the Alan Alda Center for Communicating Science (see this Wall Street Journal report explaining their work). I am trying to dissect these technologists’ skills at communication to see how others might communicate technology more effectively and honestly for more informed and necessary public discourse.
All this is why I became a loyal connoisseur of Huang’s keynotes. They are bravura solo performances: two hours or longer on stage before appreciative industry audiences, presenting new product announcements while holding up and showing off chips and boards that are, in truth, as enigmatic in their appearance and ways as an obelisk to a 2001 ape. All the while, he explains Nvidia’s accomplishments and position in the field and the market. It shouldn’t be mesmerizing, but to me, it is.
As a student of Huang’s addresses, I soon learned that in each, he has a new lesson to impart, in addition to promoting a new chip or software or deal. The first talk that really hooked me was his Nvidia developers’ conference keynote of March, 2024. In it, he helped me begin to grasp the scale of AI technology.
For a next book project on the birth and death of mass media, I’ve been reading up on the invention of the the triode vacuum tube and amplifier in 1906, which enabled radio as well as the loudspeaker. Four decades later, the tube was superseded by the transistor and eventually, in 1958, the chip. (BTW, if you’re interested in that history, I recommend Conquering the Electron: The Geniuses, Visionaries, Egomaniacs, and Scoundrels Who Built Our Electronic Age by Derek Cheung and Eric Brach.)
On stage in 2024, Huang announces a new, bigger chip — a GPU or graphics processing unit named Blackwell — that holds 208 *billion* transistors shunting electrons and with them logic and knowledge. Then AI-generated animation on the giant screen behind him multiplies those chips in racks and in turn multiplies racks—each component clicking into place with satisfying, synthetic clunks — to add up to an entire data center populated with 32,000 GPUs — thus six quadrillion transistors. Mind blown. Here is that moment, beginning at minute 26:
Huang’s lesson in that keynote is the value of scale, for the wonders of generative AI have been made possible not only by Google’s theoretical breakthrough in 2017 but by the massive computing power (“compute” in their abbreviated argot) powered by Nvidia’s processors (and megawatts).
In that and subsequent keynotes, Huang imparts more lessons. He lectures on the economy of tokens — generative AI’s numerical abstractions of words, for instance, which LLMs create to calculate their predictions. He explains the need to manufacture tokens at ever-high speed and ever-lower cost in the data centers he characterizes as factories (of tokens). He declares the end of Moore’s Law, which since the 1960s predicted the rate of growth of the number of transistors on a chip: a 100x increase in computing power every ten years. Huang touts instead what he calls accelerated computing, boasting that Nvidia’s chips and its CUDA software platform have multiplied computing power 1,000x in just eight years.
I am transfixed as he animates the idea of digital twins: how AI, trained on a massive number of possible scenarios, computes every alternative that could next face a factory robot or an autonomous car. (I am so taken with the idea of the digital twin that I keep imaging there’s a novel in it: the machine that predicts the consequences of every choice we face.) It is clear from what he shows off that Huang believes robotics represents the next industrial explosion.
Last fall, Huang gave a keynote to Nvidia’s Washington conference, in which he deftly thanks the Trump administration and Department of Energy for helping his industry’s cause, without sacrificing a gold bar or too much dignity. Here he wants to teach policymakers about the needs of the industry that is holding up our economy even with tariffs and war.
It turns out Huang is not just a presenter but also an effective debater. See him here making his case for allowing sales to China as a benefit to American industry, in this podcast with Dwarkesh Patel.
Huang took a company that began making chips to power computer — and particularly game — graphics and positioned it to be at the heart of the AI explosion, its market valuation exceeding $5 trillion. If anything would give a CEO license to make outlandish claims and predictions, that would. But Huang doesn’t talk about flying to Mars. Instead, he tries to explain the value of what is being built. To his DC audience, he asserts that “AI is not a tool. AI is work. AI is work that can use tools.” I think that is new.
If you’re hooked now like me, watch his latest California keynote, in which he talks about the agentic age suddenly upon us.
Yann LeCun is a different kind of communicator. He is first and foremost a researcher and educator, secondarily now an entrepreneur. I have tried to read and watch his presentations to NYU students and I must confess that not too long in I regret my success at dodging higher mathematics courses … in high school. Yet LeCun is also an effective communicator even to humanities dolts like me. Here he is a year ago patiently explaining his perspective on AI to Jason Howell and me on our podcast, AI Inside:
Getting to speak with LeCun is a privilege, for he is one of AI’s godfathers (though, as he says, living in New Jersey, he’d prefer a different honorific). Among his many accomplishments and recognitions, he has received— alongside Yoshua Bengio and Geoffrey Hinton — the 2018 Turing Award for work on deep learning.
What I value most about listening to LeCun is that he does not suffer bullshit, whether that is claims of imminent superintelligence or prognostication of inevitable disaster for jobs or humankind itself. As a clear-eyed academic, he never shies away from debate or disagreement rooted in research.
Lately, LeCun has developed a reputation as a contrarian regarding LLMs, though his is a view he has long held. While the putative Wunderkinder of the infant industry — the leaders of OpenAI, Anthropic, et al — insist that all they need is ever-more compute to reach their Everest of so-called artificial superintelligence (any day now), LeCun argues persuasively — to me — that LLMs, though impressive and useful, are essentially a dead-end, for they traffic in text, which represents a finite sphere of representation of life.
LeCun has argued instead for devising world models to teach the machine the sort of experiential constraints a toddler or a kitten can learn: about gravity acting upon a ball falling off a table, where it persists, though now unseen. If one wants to build AI for the real world, one must conquer Moravec’s paradox: that “it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility.” This from LeCun’s presentation:
For an effective starter course in LeCun’s worldview, I highly recommend watching him debate LLMs vs. world models with Google DeepMind’s Adam Brown, in this Scientific Controversies discussion moderated by Janna Levin at Brooklyn’s Pioneer Works.
In 2022, LeCun published a paper proposing a “path towards autonomous machine intelligence… enabling them to reason, predict, and plan at multiple time horizons… [as] intelligent agents.” Or as he sums up the goal: to work with common sense. Here, too, is a 117-slide presentation he made to NYU students explaining his ideas. I’ll admit I am soon lost in the formulae, though the lecture isn’t meant for the likes of me. This is how he instructs students, fellow computer scientists, competitors — and now funders, as LeCun has founded AMI Labs to build advanced machine intelligence on his model for the future, which he calls Joint-Embedding Predictive Architecture (JEPA).
I will do a bad job summarizing his proposal; that’s why I offer the videos below, for they are far more effective at communicating the ideas than I am. But in short, LeCun describes using photos and videos from real life to train models — or to train them to train themselves — so they understand representations of the world and consequences of actions, rather than trying to predict every pixel or merely ape human teachers. That is, his method can discern, say, a ball as a ball and predict the result of action on it. JEPA does this by encoding an original image alongside a corrupted version so the system can, in LeCun’s words, “predict the representation of the original image from the representation of the corrupted one.”
The implications are many. LeCun says JEPA will lead to models that can undertake a wider variety of tasks with less training, for they do not need to be taught every possible permutation of a situation. These models are also more efficient, for they concentrate attention on particular change — a ball thrown — rather than every change — countless leaves rustling in the scene — and need not predict the progress of every pixel.
He says these systems will be capable of thinking. Unlike LLMs, they won’t — at first — listen or talk, which might make them less flashy than ChatGPT or Claude: fewer neat parlor tricks to convince journalists that they’re in love. But LeCun convinces me that being able to understand the world and its constraints and to operate in it is table stakes for the next paradigm of AI. This is what it will take for AI to deliver value to industry, including in robotics, industrial control, and health care. He also is persuasive when he argues that his framework will be safer than LLMs, for rather than producing the general machines that their creators claim can do everything better than all of us — as the AI boys insist — JEPA will produce specialized agents with bounded tasks, each built to “anticipate the consequences of its own actions.” JEPA won’t take over the world. LLMs, LeCun says, can be dangerous; haven’t we learned that?
He says he is building “AI for the real world” — that is, world models — for as it turns out, “reality is way more complicated than language.”
If you want to dig into LeCun’s view of AI’s future (and understand why, on my podcasts, I regularly declare myself on Team Yann), here is a series of videos, stepping up in complexity. The first is a casual conversation with Jacob Effron:
Next is a more technical and deeper explanation of JEPA from Welch Labs. I had to watch a few times to understand some (not all) of it. It is an excellent primer (and here is part 2.
And here is a video in which LeCun does not speak. It is a victory lap for his vision of building reasoning: building a system that can solve any problem given a set of constraints rather than just generating a next token (or writing a brute-force, old-fashioned program). The host, Ksenia Se of Turing Post, extols JEPA (but notes that it is “quite a tragic name for a beautiful idea”).
Note the title of the video: “Yann was right.” To which Yann added when he shared it on his socials, “But of course I was.” (That’s another reason I like both these men; they have a sense of humor that is not evident in the other AI boys.)
What I most appreciate about LeCun is the humility inherent in a scientist’s worldview. The generative AI companies display the hubris of believing they are almost done building the general machine that can take over every human task, or destroy us in the process. LeCun is, instead, on a scientific journey of discovery and iteration. He knows there is yet much work to be done.
I also greatly respect his support for open source. When he was at Meta, heading a lab and then advising on AI, he fought for it to release its Llama models openly. This is how academics and scholars work: inviting challenges, teaching others, and collaborating and learning together.
AI is here to stay. There is no wishing or protesting or regulating or boycotting it away. We must not surrender its future and ours to a few oligarchic billionaires. The only way we can have a voice in its direction is to understand it better. And the only way we can understand it is by listening critically to the people actually building it. That is why I want to see technologists better able to communicate about technology — so we can debate it and its effects. That’s why I’m studying these two masters of communication.
Eddie Glaude, Jr., holds a mirror up to America. Look, he tells us, look! How often I have heard him on television, invited to the camera by Nicolle Wallace to lament another American tragedy and sin: racist murders, the shooting deaths of mere babies, the abuse of immigrant children, the bigotry of the president. Do not say that this is not us, he demands. This is us. This is America. The italics are his. Unless and until we, we white Americans, acknowledge and absorb that truth, he tells us, we cannot and never will move past it.
Glaude’s new book, America, U.S.A.: How Race Shadows the Nation’s Anniversaries, is that mirror, reflecting the worst of our reality in sharp detail. He uses the moment of the nation’s already spoiled 250th anniversary to look back on earlier birthdays, on earlier assertions of an American ideal that were always in fact claims to a white America. Those claims have met their lowest ebb in Donald Trump and his klan’s brazen denials of the nation’s racism and any remedies. Diversity is as much as illegal. Racism is now the de facto law of the land.
His book is a stunning, damning indictment and conviction of our nation. I cannot recommend it more highly. Best yet, I commend you to listen to the audiobook, read by Glaude. More than once over the years, at the beginning of a Princeton term, I have wandered through the downstairs stacks in my favorite bookstore, Labyrinth, to see what texts are being assigned in the classrooms across the street. I always stop at the shelves filled with those selected by Prof. Glaude, wishing I could sit in his class and learn. To hear him read this book is to witness his teaching.
While I was listening to the book, I joined Julie Roginsky and Michelle Kinney for our every-Friday lament about the state of news and media in the podcast we call Breaking the News. What was most broken last week was, of course, CBS. As we were cursing the murder of 60 Minutes at the hands of Bari Weiss and the Ellisons, Michelle said something most wise: that sometimes, rather than wishing to recapture what is lost, we must simply mourn it.
Yes, 60 Minutes is the dead show walking. CBS News is already dead. CNN is likely doomed. The Washington Post might as well be buried. The New York Times fails us constantly in the face of fascism. Sinclair is brainwashing towns across the nation, where hedge funds have ruined most every newspaper. Ultimately, I contend, it is mass media that is dead and doesn’t know it. I no longer think it is worthwhile to wonder how to fix it. Instead, I mourn it and ask what will replace it.
In this context, I brought up Glaude’s book and said that he forces me to mourn not an America that was but an America that never was: a fantasy of the nation.
My grandparents were, frankly racist. And so I was proud of my parents for raising my sister and me to recognize and reject their way of thinking. But what my parents wanted to replace it with in my mind was the American myth of the melting pot. It was too many years later that I saw the inherent falacy in the contention that harmony would come at the expense of identity and history, as if we in power, we white Americans, would ever admit others into our pot of privilege. To be colorblind, as was the aspiration of the time, was to be blind to history, to the effects of racism and the benefits of our own birth.
Just as I see that in my own field, to which I have devoted fifty years of my life, it is fruitless and ultimately delusional to think there ever was something better to return to, so I understand that an America of principles can only be built anew, following the full realization of what it was and still is. Each must be replaced.
What Glaude forces his readers to do is to face the reality of racist America, the crusade to declare the U.S.A. a white nation and to exclude all others. He calls us to a radical new birth. It is brilliantly written, forceful in its poetry, unflinching in its honesty, demanding in its teaching.
Soft-spoken, unassuming, humble, kind, and generous, Don Newhouse was at the same time a publisher of vast experience, universal respect, and great strength. I had the great privilege of working for him via his sons, Steven and Michael, at various tasks in the newspaper, magazine, cable, and book arms of the media empire he built with his brother, Si. I entered at a moment of volcanic change in our industry, starting in 1994, just as the commercial browser was introduced and the company decided to forego Prodigy, AOL, et al for this new world wide web.
One clear memory of mine is sitting at a table in Don’s unpretentious Newark office in the Star-Ledger with the family members who oversaw the newspapers, each of them traveling to a different paper and city each month. Thus they were called “The Travelers.” That day, one of the many new competitors to newspapers for their long-lucrative classified business, Monster.com, had reported declining earnings. Don would brook no gloating. He pounded the table to get attention and announced sternly, “People! It’s not coming back.” While others in the industry maintained false hopes, Don was clear-eyed and strategic about the future. He bravely invested in that future.
Under Donald, Steve, and Michael, Advance cut its own path. While others in the industry made online an afterthought next to their legacy newspapers, Advance set up separate companies so their digital entities could explore and exploit every advantage of the internet — experimenting with new models for content and business. We established new brands, including NJ.com and Cleveland.com (URLs the company had the foresight to grab). We were the most interactive of any newspaper-related sites; it was Steve who taught me the value of conversation and connection — more than content — online. Don once told a friend of mine, “Jeff learned everything he knew from Steve.” True that.
It is hard to imagine that there was a time when no one could be sure whether this online/internet thing would last. Just as newspapers, magazines, and books jockeyed for advantage in the early industrialization of American media at the turn of the prior century, so in its digitization at the turn of this century, it was not clear whether print or digital would emerge triumphant. But there came a time when the victor was clear. After I left Advance in 2005 to help start a new journalism school at CUNY, I was brought back to work on a daring project in Ann Arbor.
Another memorable day was spent in a large conference room at Condé Nast’s Times Square headquarters as executives presented the owners with various scenarios for the future of print: what happens if circulation falls by X percent or advertising by Y. It was there and then that Donald and his family and managers decided to take the brave step of making Ann Arbor their first digital-first market, turning the company’s outlet in town into a fully online entity with a newspaper as an ancillary product. Eventually, most every newspaper company would follow Advance’s lead. It was a wrenching decision. I recall witnessing the courage and poignance of that moment. Here was the beloved newspaper company Donald and Si and their generation had inherited from their father and founder, Sam: a precious family heirloom. They loved their newspapers, their histories, and everything they stood for. But as I said, Don was a strong and strategic executive who knew he had to preserve the company and the journalism, not necessarily the presses.
Don was not just a dedicated publisher but also, of course, a doting husband to his beloved Sue, who died in 2015, father to Steve and Michael, and grandfather as well. Other media dynasties have failed to pass down their companies and knowledge to following generations. Not the Newhouses. I watched with enduring admiration as Steve and Michael continued every day to respect and learn from their father, carrying on not just the business but the values and experience that made them and their company stand apart. I am forever grateful for every lesson I learned in turn.
Pope Leo XIV’s encyclical, Magnifca Humanitas, is a learned, wise, eloquent, and useful document that is only partly about artificial intelligence. Its lessons should be helpful to many modern institutions — including my own, journalism.
For those expecting the Pontiff to declare holy war on AI and Silicon Valley, they will be disappointed. Those who wish to claim AI as a new religion will be similarly bereft. Apart from a few timely and almost obligatory references to children and screens, this is not a document influenced by the moral entrepreneurs seeking to inflate and exploit fears of technology. Though it calls for regulation, it does not attempt to prescribe statutes. This is a document intended for generations, to inform our discourse as we manage secular upheaval. I will quote liberally, though I recommend reading it in full.
Leo opens with an apt Biblical metaphor, contrasting the Tower of Babel with the rebuilding of the walls of Jerusalem. Babel was a doomed project of immense hubris, constructing a tower to the heavens. “It was an impressive feat: a single language, a single technology, a single direction,” he writes. “However, the project concealed a profound danger: It was a project conceived without reference to God, supported by uniformity that eliminated diversity and that chose homogenization over communion.” That does sound familiar these days.
The rebuilding in Jerusalem, on the other hand, was undertaken following prayer and permission with the people of the city collaborating through acts of listening and communion. Leo’s encyclical is a profound testament to the value of community — a lesson I try to teach to students of media.
Leo goes to pains to make clear that “technology should not be considered, in itself, as a force antagonistic to humanity.” Quoting Pope Benedict XVI, he continues, “On the contrary, it has formed part of our history since the beginning as ‘a profoundly human reality, linked to the autonomy and freedom of man.’” He continues:
Technology has the power to heal, connect, educate and protect our common home; but it can also divide, exclude and generate new forms of injustice. In the abstract, technology in and of itself is not a solution to humanity’s problems, just as it is not inherently evil. In practice, however, technology is never neutral, because it takes on the characteristics of those who devise, finance, regulate and use it. Therefore, the primary choice is not between a “yes” or “no” to technology, but rather between constructing Babel or rebuilding Jerusalem; between a power that claims to dominate the heavens and a people who work together in the presence of God to rebuild the walls of fraternal coexistence.
He calls for technological innovations, including AI, to “be evaluated by asking a crucial question: Do they truly help individuals and peoples to become more humane and fraternal, while respecting our common home and future generations?”
Leo warns of unprecedented control by private, transnational corporations that monopolize “expertise, data, and decision-making authority;” and of the “risk of being misled by deceitful goals, such as the prospect of a technology that promises to free us from all weakness;” and of the danger that “persons end up being reduced to a means of achieving results, a resource to be used and exploited, and are no longer recognized as a proper end in themselves who should never be instrumentalized.” He prescribes the means to instead claim agency and shared responsibility to build for the common good, “so that humanity will never lose its beauty.”
The civilization of love will not arise from a single or spectacular gesture, but from the sum total of small and steadfast acts of fidelity that serve as a bulwark against dehumanization. For this reason, it is worthwhile pausing to reflect on some aspects of how we, each in our own way, can cooperate in building the civilization of love. Without presuming to exhaust this theme, I would like to propose five paths toward daily and public responsibility: the need to disarm words, building peace through justice, adopting the perspective of victims, cultivating a healthy realism and reviving dialogue and multilateralism.
Generously quoting his predecessors to trace the history of the Social Doctrine of the Church — from Rerum Novarum through the Second Vatican Council to Pope Francis — Leo lays his foundation with sets of principles that guide the Church as a model for other institutions: “listening, dialogue, and service … the dignity of every person, the cohesion of communities, and the good of all … the contributions of philosophy and of the human and social sciences … the importance of listening to scientific research and of encouraging a serious and honest debate among experts while welcoming a diversity of opinions … justice … Understanding that the truth is a gift to be shared, not a possession to be monopolized.”
As a journalist, that last observation on truth struck me. Journalists like to think they traffic in truth and — especially now in fights with AI companies over copyright — publishers claim ownership of it. Shouldn’t news organizations follow the same advice Leo gives to technology companies: that “truth is a gift to be shared, not a possession to be monopolized…. In this way, the truth of the Gospel is not imposed from above, but grows over time within the concrete interweaving of lives, communities, and cultures. This is not a truth that fears diversity, but instead welcomes and guides it. It does not eliminate conflicts, but transforms them, reuniting that which history tends to scatter.” Truth is too precious to hoard or sell.
In discussing the power of technology companies, I believe Leo is also, if unwittingly, describing the exclusionary power that mass media have wielded over the last century:
These entities effectively set the conditions for access, determine the rules of visibility and shape the very possibilities for participation. When such power is concentrated in the hands of a few, it tends to become opaque and evade public oversight, increasing the risk of distorted forms of development that give rise to new dependencies, exclusions, manipulations and inequalities.
It is not until halfway into his encyclical that Leo directly addresses artificial intelligence and “the danger of humanity becoming a victim of its own achievements,” saying he does not intend to offer a comprehensive treatment of the technic but wishes to “ensure that it will always be human intelligence, with its conscience and freedom, that guides technical innovations and responsibly determines their use and limits.”
Nor does Leo try to define artificial intelligence, though by examining — and defending — human intelligence, he defines what it is not.
[W]e must avoid the misconception of equating this type of “intelligence” with that of human beings. These systems merely imitate certain functions of human intelligence. In doing so, they often surpass human intelligence in speed and computational capacity, offering tangible benefits across many fields. Yet this power remains entirely tied to data processing. So-called artificial intelligences do not undergo experiences, do not possess a body, do not feel joy or pain, do not mature through relationships and do not know from within what love, work, friendship or responsibility mean. Nor do they have a moral conscience, since they do not judge good and evil, grasp the ultimate meaning of situations, or bear responsibility for consequences. They may imitate language, behavior and analytical skills, or even simulate empathy and understanding, but they do not understand what they produce, for they lack the affective, relational and spiritual perspective through which human beings grow in wisdom. Even when these tools are described as capable of “learning,” their way of doing so is different from that of a human person. It is not the experience of those who allow themselves to be shaped by life and grow over time through choices, mistakes, forgiveness and fidelity. Rather, it is a form of statistical adaptation based on data and feedback, which can be very effective, but does not imply inner growth.
In his rejection of the claims of machine sentience, consciousness, or — God save us — life, I am on Team Leo: this is impossible, technically and definitionally. I am grateful to see the Pontiff directly reject transhumanism (“the enhancement of human beings through technologies — such as biomedicine, body engineering, devices and algorithms”) and posthumanism (which “challenges anthropocentrism and envisions a hybridization of human beings, machines and the environment, even anticipating a threshold where humanity surpasses itself in a new evolutionary stage”). In short: playing God. These are the quasireligious beliefs of some AI cultists, bundled into the acronym #TESCREAL (Google it). Leo further also calls out media for credulously covering these claims.
These perspectives form the ideological background present in some centers of technological power and occupy the collective imagination in a simplified form, especially in the media and on social networks. They tend to foster enthusiasm for new technologies through a futuristic vision of an “enhanced human being” or “human-machine hybrid.”
Therein hangs the odious stink of eugenics.
If the human being is treated as something to be perfected or surpassed, it becomes easier to accept that some lives are less useful, less desirable or less worthy. In the name of progress, “necessary sacrifices” may begin to be justified, placing the burden on the most vulnerable in pursuit of a supposed optimization of the species. In this regard, the aforementioned warning of Saint Paul VI retains great foresight: indeed, scientific and technological advances, when detached from moral and social progress, end up turning against humanity. For this reason, a clear distinction must be made. It is one thing to integrate technology within a human-centered, relational vision; it is quite another to be guided by an outlook that devalues human limits and promises a purely technical form of “salvation.”
So it is well and good — necessary, actually — that Leo examines the nature of human life and collective humanity in the context of AI.
When we embrace the possibility of transcending ourselves through God’s grace, we do not deny our nature, nor do we become less human. On the contrary, as Pope Francis explained, “We become fully human when we become more than human, when we let God bring us beyond ourselves in order to attain the fullest truth of our being.” Herein lies the radical departure from Promethean dreams: what saves humanity is not enhanced self-sufficiency, but a relationship that liberates, a communion that transforms. In this light, a technology that merely classifies and optimizes what already exists can, however unintentionally, become an obstacle to change and growth. For an algorithm, an error is a flaw to be corrected; for a person, however, an error can be a catalyst for profound change. A person’s future is not calculable, but depends on one’s freedom — elevated by the inexhaustible grace of God — and on the relationships cultivated.
In his exploration of artificial intelligence and its effects, Leo returns to the subject of truth in the context of democracy, noting that disinformation has been around long before the accelerating technology of AI. “Truthful information,” he observes, “does not arise from centralized or automated control.” Again, the lesson is not just for AI but for mass media, which has been centralized and controlled since its mechanization and industrialization at the turn of the prior century. (That is the subject of my upcoming book, Hot Type.)
Then Leo adds an observation that leaves me applauding: that truth in public discourse “is deeply relational, built through bonds of trust and shared practices, as well as an honest exchange with others and with the world. Only the shared pursuit of the veracity of facts, perceived as a common good, can provide a solid foundation for just communication.”
In my research for my prior book, The Web We Weave, I researched what people did to ferret out truth before the invented institutions of editing and publishing imbued the technology of print with authority. I came across the concept of FAMA — Latin for “it is said,” the root of the words “fame” and “infamy” — a social system of maintaining one’s reputation for credibility as source, subject, object, or teller of information. Our print institutions turn out to be inadequate to the scale of speech today, so out out of necessity, we are are left to return to such a system of social responsibility. We as a society are out of practice with judging truth on our own, having been told it could be handed to us by media that claimed ownership. That was always an abdication of responsibility. “Indeed, dialogue is an ordinary part of human life,” says Leo. “It involves acquiring an attitude that seeks to forge bonds of fraternity built on listening, an open demeanor, making time for each other and even wasting time together.”
I am gratified that Leo cites Arendt on the subject. “Indifference to the truth leads, slowly but surely, to a descent into totalitarianism. As the philosopher Hannah Arendt wrote, the ideal subjects of such regimes are not so much those who are ideologically convinced, but rather ‘people for whom the distinction between fact and fiction (i.e., the reality of experience) and the distinction between true and false (i.e., the standards of thought) no longer exist.’” He adds: “When people come to believe that nothing is genuinely true and that principles are hollow words, then the fuse in their hearts is lit for new eruptions of intolerance and aggression.”
I am also tickled to hear Leo sounding positively McLuhanesque when he discusses “an ecology of communication,” recognizing, in terms James Carey might approve of, that communication “is not only the transmission of information, but it is also the creation of a culture.” This is the premise of my book, The Gutenberg Parenthesis: that before and after the age of print — both in the time of FAMA and in the age of the internet — public discourse and public opinion are emergent from the public, rather than imposed upon a mythical, monolithic mass. How we use these tools and powers again is up to us.
Leo has much to say about the value of education and schools in the age of AI: “We must learn, then, how to exercise restraint in the use of AI and to protect our young people from the promise of the perfect machine, from that subtle temptation which renders human thought seemingly superfluous precisely when it is most needed.”
He has much to say about technology in the economy, decrying “finance for its own sake” and the metric of GDP, which neglects “aspects essential to the overall wellbeing of people and the environment. He cites Pope Francis, who denounced
the growing dominance of a technocratic paradigm in our globalized world: the tendency to let the logic of efficiency, control and profit alone shape personal, social and economic decisions. This makes it clear that technology is not simply a tool. When it becomes the standard by which everything is judged, it begins to dictate what matters and what can be discarded, reducing creation to an object of exploitation and human beings to mere cogs in a system driven toward ever greater efficiency.
And he worries about the dignity of work — including that which goes into the making of AI — and makes clear that the Church has long supported labor and unions.
Today, the convergence of automation, robotics and AI is rapidly transforming the very structure of work. It is said that this will bring great improvements for everyone. In reality, however, the “new ways” of working are not necessarily better, for “while AI promises to boost productivity by taking over mundane tasks, it frequently forces workers to adapt to the speed and demands of machines, rather than machines being designed to support those who work. As a result, contrary to the advertised benefits of AI, current approaches to technology can paradoxically de-skill workers, subject them to automated surveillance and relegate them to rigid and repetitive tasks. The need to keep up with the pace of technology can erode workers’ sense of agency and stifle the innovative abilities they are expected to bring to their work.” Precisely in order to avoid this drift, it is necessary to design systems that are centered on the human person and not solely on performance.
Some in AI-Land argue the solution to a de-skilled and unemployed workforce is universal guaranteed income. Leo would seem to disagree.
For these reasons, work is not simply an instrument; it expresses and enhances the dignity of our lives. It is a requirement of the human condition, a normal path toward maturity, development and personal fulfilment. In this regard, financial assistance to the poor may at times be necessary in emergencies, but it cannot become the sole response, since the goal is to enable each person to live with dignity through his or her own work.
The Vatican invited a co-founder of Anthropic to speak alongside the Pope, On the one hand, Anthropic presents itself as the good AI company, its leaders standing on conscience to prevent their tools being used as autonomous weapons of death. It promises that its models’ behavior will be aligned with its “constitution.” Then again, I have long argued that to believe an AI model can be imbued with ethics, let alone guardrails, is a fool’s errand, for — just as with Gutenberg’s type — there is no way to anticipate and prevent every possible malign use of a technology. It was, after all, movable type that opened the door — did not cause but made possible — the Reformation. Ethics cannot be baked into a machine; ethics must inform our use of it. Leo writes:
It is not enough to invoke ethics in the abstract; robust legal frameworks, independent oversight, informed users and a political system that does not abdicate its responsibility are required. Otherwise, change will be governed only by technocratic thinking and presented as necessary and inevitable, ultimately imposing rules shaped by those who control data, infrastructure and computing power. We cannot be satisfied with merely calling for the moralization of machines — the so-called “alignment” of AI with human values — without also having the courage to insist on a further condition: the possibility of openly discussing the ethical frameworks involved and subjecting them to shared standards of social justice. Otherwise, those who control AI will impose their own moral vision, which will become the invisible infrastructure of these systems. A more moral AI is not enough if that morality is determined by a few.
The impossibility of technology’s moral autonomy is particularly potent given the state of technology and war.
Sometimes there is talk of “artificial moral agents,” as if machines were able to distinguish between right and wrong with greater consistency than a human being. Yet moral judgment cannot be reduced to calculation, for it involves conscience, personal responsibility and the recognition of the other as a person. Therefore, it is not permissible to entrust lethal or otherwise irreversible decisions to artificial systems. No algorithm can make war morally acceptable. AI does not remove the intrinsic inhumanity of conflict; indeed it can only bring about conflict more quickly and render it more impersonal, lowering the threshold for resorting to violence, transforming defense into threat prediction and thus reducing victims to data. In this way, it will accustom us to the idea that violence is inevitable and needs only to be optimized.
In the end, the encyclical is a meditation on technology, power, and justice.
Indeed, entrusting an algorithm in practice with the power to select who is worthy or not, without anyone bearing responsibility for that judgment, is to hand over the task of redefining the boundaries of human possibilities…. From this follows a simple but compelling consequence: we cannot consider AI to be morally neutral. In reality, every technical tool embodies choices and priorities through what it measures, ignores and optimizes, and how it classifies people and situations. If a system is designed or used in a way that treats some lives as less worthy, or excludes them without the possibility of appeal, then it is not merely a tool “to be used well,” since it has already introduced criteria that contradict the inalienable dignity of the human person. For this reason, ethical discernment cannot be limited to asking whether we are using a system for good or bad purposes; it must also examine how that system is designed and what vision of the human person and society is embedded in the data and models that guide it. For AI to respect human dignity and truly serve the common good, responsibility must be clearly defined at every stage: from those who design and develop these systems to those who use them and rely on them for concrete decisions.
Yes. Responsibility for AI rests not only with its creators but also with every user, with all of us. It is critical to end noting that Leo’s encyclical has much positive and constructive instruction on ways to responsibly use and manage the technologies of the age with transparency, accountability, choice, and justice.
At this point, however, a subtle temptation may emerge, namely the thought that the problems are too big and we are too small, and that our choices, therefore, cannot make a difference. This is a polite form of resignation, often disguised as realism. Certainly, not everyone has the same power to make a difference. There are those who govern, make investment decisions, lead institutions, conduct research, educate, produce or provide information, and then there are those who only seem to live their daily lives. Yet, no one is without responsibility. We all have our own areas for action, and it is precisely there — and nowhere else — that we must choose whether to fuel the mentality of force (even if only through indifference, cynicism, lies or hatred), or to preserve the mindset of peace (with truth, moderation, closeness and care).
